Structure reconstruction of correlated neural signals based on inpainting for brain monitoring

This paper presents a novel approach for compressing neural signals. This topic is especially important for the realization of implantable neural measurement systems (NMS) since they are subject to strict constraints with regard to area and energy consumption. The handling of high data rate becomes a major topic within NMS. Compared to the often applied Compressed Sensing (CS) technique an approach steaming from image restoration is applied to NMS in this work for the first time: Inpainting strategies. The proposed Inpainting approach as well as CS focus on resource efficiency on transmitter (Tx) side in NMS. It can be shown, that the proposed approach outperforms CS in terms of recovery quality and thus is a promising alternative for the realization of innovative reliable NMS.